AI Governance
Plain-language explanation
The structures, roles, decision processes, controls, and oversight an organization uses to govern AI systems across their lifecycle.
Why It Matters
AI governance connects technical systems to accountability, risk decisions, evidence, and oversight.
In Practice
AI governance is broader than an AI policy. It includes who can approve an AI use, how risks are assessed, what controls are required, what evidence is retained, and how systems are monitored or retired.
Audit and Evidence
An auditable governance program leaves reliable records of decisions, implementation, monitoring, and accountability.